JMIR Publications

ABSTRACT

Computer-assisted clinical coding (CAC) tools are designed to help clinical coders assign standardized codes, such as ICD-10, to clinical texts, such as discharge summaries. Maintaining the integrity of these standardized codes is important both for the functioning of health systems and for ensuring data used for secondary purposes is of high quality. To date, there have only been a few user studies, therefore our understanding of the role CAC systems can play in improving coding quality is still limited. The objective of the user study is to generate both qualitative and quantitative data for measuring the usefulness of a CAC system, Easy-ICD, that was developed for recommending ICD-10 codes. The user study is based on a crossover randomized controlled trial (RCT) study design. We measure the performance of clinical coders as well as the time it takes them to assign codes to both simple and complex clinical texts. We expect the study will provide us with a measurement of the effectiveness of the CAC system compared to manual coding processes, both in terms of time use and accuracy, especially for more complex texts. The planned user study promises a greater understanding of the impact CAC systems might have on clinical coding in real-life settings, and may add new insights on how to meaningfully exploit current clinical text mining capabilities, despite the limitations.